Senior Staff IT Data Engineer
| Company | Palo Alto Networks |
|---|---|
| Location | Santa Clara, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior |
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- 5+ years of experience in data engineering, with a focus on building and maintaining data pipelines and analytical solutions.
- Expertise in SQL programming and database management systems.
- Hands-on experience with ETL tools and technologies (e.g. Apache Spark, Apache Airflow).
- Experience with cloud platforms such as Google Cloud Platform (GCP), and experience with relevant services (e.g. GCP Dataflow, GCP DataProc, Big Query, Procedures, Cloud Composer etc).
- Experience with Big data tools like Spark, Kafka, etc.
- Experience with object-oriented/object function scripting languages: Python/Scala, etc.
- Strong analytical and problem-solving skills, with the ability to analyze complex data sets and derive actionable insights.
- Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
Responsibilities
- Design, develop, and maintain data pipelines to extract, transform, and load (ETL) data from various sources into our data warehouse or data lake environment.
- Collaborate with stakeholders to gather requirements and translate business needs into technical solutions.
- Optimize and tune existing data pipelines for performance, reliability, and scalability.
- Implement data quality and governance processes to ensure data accuracy, consistency, and compliance with regulatory standards.
- Work closely with the BI team to design and develop dashboards, reports, and analytical tools that provide actionable insights to stakeholders.
- Mentor junior members of the team and provide guidance on best practices for data engineering and BI development.
Preferred Qualifications
- Aptitude for proactively identifying and implementing GenAI-driven solutions to achieve measurable improvements in the reliability and performance of data pipelines or to optimize key processes like data quality validation and root cause analysis for data issues, is a nice-to-have.
- Demonstrated readiness to leverage GenAI tools to enhance efficiency within the typical stages of the data engineering lifecycle, for example by generating complex SQL queries, creating initial Python/Spark script structures, or auto-generating pipeline documentation, is a nice-to-have.
- Experience with BI tools and visualization platforms (e.g. Tableau) is a plus.
- Experience with SAP HANA, SAP BW, SAP ECC, or other SAP modules is a plus.